Climatological aspects of aerosol optical properties in Northern Greece

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Climatological aspects of aerosol optical properties in

Northern Greece

E. Gerasopoulos, M. O. Andreae, C. S. Zerefos, T. W. Andreae, D. Balis, P.

Formenti, P. Merlet, V. Amiridis, C. Papastefanou

To cite this version:

E. Gerasopoulos, M. O. Andreae, C. S. Zerefos, T. W. Andreae, D. Balis, et al.. Climatological aspects of aerosol optical properties in Northern Greece. Atmospheric Chemistry and Physics Discussions, European Geosciences Union, 2003, 3 (2), pp.2059-2099. �hal-00303883�

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Atmos. Chem. Phys. Discuss., 3, 2059–2099, 2003 www.atmos-chem-phys.org/acpd/3/2059/

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European Geosciences Union 2003

Atmospheric Chemistry and Physics Discussions

Climatological aspects of aerosol optical

properties in Northern Greece

E. Gerasopoulos1, 2, M. O. Andreae2, C. S. Zerefos1, T. W. Andreae2, D. Balis1, P. Formenti3, P. Merlet2, V. Amiridis1, and C. Papastefanou4

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Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, P. O. Box 149, 54124 Thessaloniki, Greece

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Max Planck Institute for Chemistry, Biogeochemistry Department, P.O. Box 3060, 55020 Mainz, Germany

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Centre of Geophysics of ´Evora, Universidade de ´Evora, Rua R. Ramalho, 59, 7000-532 ´

Evora, Portugal

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Nuclear Physics Department, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Received: 27 November 2002 – Accepted: 21 March 2003 – Published: 15 April 2003 Correspondence to: E. Gerasopoulos (egera@skiathos.physics.auth.gr)

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Abstract

Measurements of aerosol optical properties (aerosol optical depth, scattering and backscattering coefficients) have been conducted at two ground-based sites in Northern Greece, Ouranoupolis (40◦230N, 23◦570E, 170 m a.s.l.) and Thessaloniki (40◦380N, 22◦570E, 80 m a.s.l.), between 1999 and 2002. Their frequency

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tions have revealed the presence of individual modes of high and low values, indicating the influence from different sources. At both sites, the mean aerosol optical depth at 500 nm was 0.23. Values increase considerably during summer when they remain per-sistently between 0.3 and 0.5, going up to 0.7–0.8 during specific cases. The mean value of 65±40 Mm−1of the particle scattering coefficient at 550 nm reflects the impact

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of continental pollution in the regional boundary layer. Trajectory analysis has shown that higher values of aerosol optical depth and the scattering coefficient are found in the east sector (former Soviet Union countries, eastern Balkan countries), whereas cleaner conditions are found for the NW direction. The influence of Sahara dust events is clearly reflected in the Angstr ¨om exponents. About 45–60% of the observed diurnal

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variation of the optical properties was attributed to the growth of aerosols with humidity, while the rest of the variability is in phase with the evolution of the sea-breeze cell. Lo-cal pollution is estimated to contribute 35±10% to the average aerosol optiLo-cal depth at the Thessaloniki site during summer. Finally, the aerosol scale height was found to be related to the height of the boundary layer with values between 0.5–1 km during winter

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and up to 2.5–3 km during summer.

1. Introduction

The role of aerosols in a changing climate has been under scrutiny during the past decades (e.g. Coakley et al., 1983; Andreae, 1995; Penner et al., 2001; Haywood and Boucher, 2000). Depending on their intrinsic properties, especially the single scattering

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the greenhouse gases which only cause warming. Nevertheless, the “level of scientific understanding” concerning the various climatic effects of atmospheric aerosols is still very inadequate (Houghton et al., 2001; Shine and Forster, 1999).

In the last decade, a substantial number of experimental studies on aerosols have focused on the eastern Mediterranean area (Luria et al., 1996; Pinker et al., 1997;

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halopoulos et al., 1997; Paronis et al., 1998; Papayiannis et al., 1998; Ichoku et al., 1999; Andreae et al., 2002; Formenti et al., 2001a; 2001b; 2002a; 2002b; Lelieveld et al., 2002; Kouvarakis et al., 2002). This is because of the maximum in the net di-rect radiative forcing by sulfate aerosols predicted to occur in this region by various models (Charlson et al., 1991; Kiehl and Rodhe, 1995; Boucher and Anderson, 1995).

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Accumulation of aerosols and enhanced backscattering is favored by the meteorolog-ical conditions prevailing over the eastern Mediterranean, namely sparse cloudiness and prolonged exposure to solar radiation. Concentrations of important trace gases and aerosols are typically factors of 2 to 10 higher over the Mediterranean than in the hemispheric background troposphere (Lelieveld et al., 2002). Within the eastern

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Mediterranean, the Aegean sea and the coastal part of continental Greece are in a “key” geographical position where aerosols from different sources converge, namely maritime aerosols from sea spray; mineral dust from North Africa; and anthropogenic aerosols from the highly populated urban centers and industrial areas, as well as sea-sonal biomass burning (Formenti et al., 2002a, 2002b). In the lower troposphere over

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the Mediterranean, European pollution is mainly responsible for the reduction of air quality, particularly during summer, whereas in the free troposphere pollution is largely determined by intercontinental transport (Lelieveld et al., 2002).

Furthermore, the impact of aerosols on the photochemical activity and thus on the air quality of the region is very important and has been studied extensively during the

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tochemical Activity and Ultraviolet Radiation (PAUR) campaigns (Zerefos et al., 2002) that took place in the Northern Aegean (1996) and on Crete (1999). These studies showed that various (in type and quantity) aerosols can modulate the solar UV radia-tion reaching the Earth’s surface in such a way that it can mask changes induced by

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total ozone itself (Kylling et al., 1997). Moreover, in the presence of high tropospheric ozone (Kourtidis et al., 2002) and high absorbing aerosols from the Sahara desert, re-duction in the UV and in associated photolysis rates have been measured even if total ozone decreases (Balis et al., 2002).

In this paper, we present the results of an extended time series (1999–2002) of

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measurements of the optical characteristics of aerosols (optical depth, scattering and back-scattering coefficient, Angstr¨om exponent, backscatter ratio), and thereby estab-lish a climatology of aerosols in the region. Following the description of the instru-mentation and data analysis methodology (Sect. 2), the basic statistical properties of the measured and calculated quantities are presented together with their frequency

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distributions (Sect. 3.1). In Sect. 3.2, the source distribution of aerosols with different properties is investigated via air mass trajectory analysis. The temporal variation of aerosol optical properties for two time-scales, seasonal and diurnal, is then described (Sects. 3.3, 3.4, respectively), and finally an estimation of the contribution of local pol-lution sources (Sect. 4.1) and of the aerosol scale height (Sect. 4.2) is attempted. The

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following notation for the optical properties of aerosols will be used in the text: AOD= aerosol optical depth,

˚a_τ = Angstr¨om exponent calculated from aerosol optical depths at different wave-lengths,

σ_sp= scattering coefficient,

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σ_bsp= back-scattering coefficient,

˚a_σ = Angstr¨om exponent calculated from scattering coefficients at different wave-lengths,

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2. Instrumentation and methodology

2.1. Site description

Measurements of aerosol optical properties have been conducted at two ground-based sites in Northern Greece between 1999 and 2002. The first station is situated in the region of Ouranoupolis (Mount Athos Observatory, MAO, 40◦230N, 23◦570E, 170 m

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a.s.l.), a rural area in the Chalkidiki peninsula, 100 km east of Thessaloniki, the closest major city with a population of approximately 1 million. The second station is located in an urban setting at the Laboratory of Atmospheric Physics in Thessaloniki (LAP, 40◦380N, 22◦570E, 80 m a.s.l.). Both sites face the Aegean Sea to the south and are situated along the expected pathway through which pollution from central and eastern

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Europe influences aerosol loading over the Eastern Mediterranean. 2.2. Instrumentation

At MAO, a multi-filter rotating shadowband radiometer (MFR-7 Yankee Env. System Inc., Turner Falls, MA) has been providing 1-min average aerosol optical depths (AOD) at five wavelengths (415, 501, 615, 675 and 867 nm) since June 1999, with a gap from

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September 2000 until June 2001 due to instrument malfunctioning. A three wavelength (450, 550 and 700 nm) integrating nephelometer (TSI 3563, TSI Inc., St Paul, MN) has been also providing continuous measurements (2-min resolution) of the particle light scattering coefficients for both total scattering (σ_sp) and back-scattering (σ_bsp) for the same period, with minor gaps from September to middle November 1999 and from April

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to July 2001. A second multi-filter rotating shadowband radiometer of the same type has been operating at LAP since February 2001. Valid measurements from the MFR were obtainable during daytime under clear sky conditions only. Gaps in the time se-ries are associated with either total cloudiness, enhanced during the fall-winter period, or with power failures at Ouranoupolis after severe weather phenomena

(thundershow-25

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performed during the period of operation. 2.3. Methods

A detailed description of the operation principles of the MFR can be found in Harrison et al. (1994a), and a considerable number of publications have suggested various algorithms for the retrieval of aerosol optical depths from measurements of the direct

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solar irradiance (e.g. Bruegge at al., 1992; Michalsky et al., 2001; Alexandrov et al., 2002). The procedure followed in the present study is described below:

At first, the Langley linear regression technique (Harrison et al., 1994b) was applied to morning and afternoon data with airmass, m, between 2 and 6. This provided us with the solar constant I_o estimated from the intercept of the regression line. This

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dure was applied to each clear-sky day that showed a log-linear relationship between irradiance and airmass, regardless of the optical depth obtained from the slope of the regression line. The solar constants were then corrected for the Sun-Earth distance (Iqbal, 1983). The inclusion of periods with high amounts of aerosols over the station produced a bias in the estimates of I_othat showed up as a positive correlation between

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optical depth (slope) and solar constant (intercept). To eliminate these biased values, a threshold value of optical depth was chosen for each wavelength, below which I_o’s de-pendence on optical depth was statistically non-significant. The remaining cases were filtered to eliminate days with significant variability of optical depth within the day, and the same days were used for all wavelengths. Finally, trend analysis on I_owas used to

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determine a possible physical deterioration of the filters or photodiode detectors, and a linear regression provided the final I_o values to be used for each wavelength along the whole period.

The Beer-Lambert-Bouguer law (I = I_o · e−τ·m) was next applied to derive instan-taneous measurements of the total optical depth (one-minute time resolution). Finally,

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aerosol optical depths (AODs) for the five wavelengths were obtained by subtracting the contribution of Rayleigh scattering and ozone absorption from the total optical depth. The wavelength dependent optical depth of Rayleigh scattering was calculated from

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the formula of Hansen and Travis (1974) using a time series of pressure available for Thessaloniki. The ozone optical depth was extracted using the ozone absorption coe ffi-cients for each wavelength and the total column of ozone available from the operation of a double monochromator Brewer ozone spectrophotometer at Thessaloniki (Bais et al., 1996), as well as from Earth-Probe Total Ozone Mapping Spectrometer (TOMS) data

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(http://toms.gsfc.nasa.gov). For the calculation of the airmass, m, we used the formula suggested by Hansen and Travis (1974). Results from different formulas (Young, 1994; Kasten and Young, 1989; Rosenberg, 1966), also taking into account atmospheric re-fraction and the effects of a spherical Earth on the atmospheric path of radiance, were compared. The average percentage difference of each airmass value calculated by the

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different formulae from their mean increased from 0.2% to 1.7% for the airmass range of 2–6 that we used.

From the 1-min resolution measurements those parts affected by cloudiness were easily identified and removed, although the presence of thin cirrus clouds inducing slight increase in optical depth was difficult to distinguish from changes in the

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spheric conditions due to aerosol loading. For this reason, the description of cloudiness available from the Hellenic Meteorological Service at Thessaloniki helped to clarify the origins of certain diurnal disturbances. Additionally, the comparison of the columnar measurements of the MFR with the in situ measurements of the nephelometer can provide some indication for the presence of aerosol layers or thin clouds at higher

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titudes. Such disturbances do not produce large changes to daily averages, but they are useful for certain case studies.

The operating principles of the TSI nephelometer as well as the methodology used to extract σ_spand σ_bspare extensively described by Andreae et al. (2002). Corrections for the angular truncation and the nonlambertian errors were performed using the

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rection equations proposed by Anderson and Ogren (1998). For σ_sp, correction was based on the Angstr ¨om exponents, ˚a_σ, whereas constant correction factors were used for σ_bsp. To provide comparability with literature values, we provide the resulting per-centage change for our data set: For ˚a_σ > 1.5 the increase of σ_spat 550 nm stays well

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within 10% and only for ˚a_σ < 0.5 it exceeds 20% (up to 27%) – an average increase

of 9%. The pattern is the same for the other two wavelengths, only with much higher dispersion of the values. On the other hand, σ_bsp are reduced by 1.8%. The change in the recalculated value of ˚a_σ (either increase or decrease) does not exceed 10% for almost the whole range of particle size, and only for ˚a_σ < 0.2 an increase up to 30%

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is found for a limited number of cases. Finally, backscatter ratios (β) decrease by 13% on average, with the decrease reaching 30–40% for ˚a_σ < 0.5.

3. Climatological investigation of aerosol optical properties

3.1. Descriptive statistics

Before proceeding to the main analysis, we present some basic statistics in order to

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summarize the optical properties of aerosols in our study region in the Eastern Mediter-ranean, and to facilitate comparison with literature values (Table 1). A collection of literature values from previous studies is available in Formenti et al. (2001b).

The wavelength dependence of optical depth at MAO and LAP is investigated for the common period (July 2001–March 2002) using the Angstr ¨om’s power law

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imation, τ(λ) = βλ− ˚a (Angstr ¨om, 1929). Values of ˚a around 1.3 are representative of continental aerosols, whereas for larger aerosols (dust, seasalt) the exponents tend to zero (Michalsky et al., 2001). As shown in Fig. 1, average ˚a_τ values for both stations, calculated from the average AOD at each wavelength, are close to continental levels with values 1.43±0.03 and 1.57±0.05 for MAO and LAP, respectively.

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The frequency distribution of all aerosol optical properties was calculated next. The resulting histograms for AOD as well as for ˚a_τare presented in Fig. 2. A rather smooth behavior was found for the LAP data, which allowed the fitting of a lognormal distri-bution for AOD and a normal distridistri-bution for ˚a_τ. For MAO the frequency distributions proved to be more complicated and the estimation of statistical parameters was subject

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that AOD has the natural cut-off value of zero, resulting in positive skewness, whereas for ˚a_τ no such physical threshold exists near the high frequency classes, and thus a normal distribution could be applied. More specifically, for LAP the lognormal fitting resulted into a mean AOD value of 0.126±0.006 (values after ± represent the stan-dard error of the parameter estimation) and a stanstan-dard deviation of 0.63±0.06. The

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Gaussian fitting for ˚a_τ gave a mean value of 1.67±0.01 and a standard deviation of 0.19±0.01. The distribution of ˚a_τ at MAO is flatter (low kurtosis) and a slight shift to lower values appears, with a mean of 1.57±0.05 and a standard deviation of 0.28±0.06. Finally, a more complex distribution is found for optical depths at MAO, although once more a lognormal distribution could be fitted, leading however to enhanced uncertainty

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to the estimation of the parameters. Instead, three distributions were fitted in order to represent three frequency modes that seem to be consistently present. A domi-nant normal distribution with a mean of 0.2 (standard deviation, std=0.11) explains the majority of the observed values, whereas for lower values a lognormal distribution at 0.066 (std=0.34) reflects the fact that the site is actually situated at a rural area

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and thus this mode corresponds to background conditions. Finally, a second normal distribution (mean=0.47, std=0.07) represents the higher values that possibly reflect either the fact that pollution events are more easily distinguished at this site or that data coverage is more complete during the warm season, with some gaps during the winter-spring months.

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Corresponding frequency distributions were calculated for σ_sp, σ_bsp, ˚a_σ and β and are presented in Fig. 3. For both σ_bsp and σ_bsp a lognormal (background conditions) and a normal distribution were fitted resulting in a mean of 28 (std=0.8), 76 (std=25) and 2.6 (std=0.7), 7.2 (std=3), respectively. Values of ˚a_σ were fitted by a normal distribution, giving a mean of 1.74±0.01 and a standard deviation of 0.26±0.02 and

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ratios were best fitted by a lognormal distribution with a mean of 0.0961±0.0007 and a standard deviation of 0.2±0.01.

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3.2. Origins of air masses arriving at the stations

In order to investigate the source regions of particles leading to elevated AOD over Northern Greece, back-trajectories (96 h) were calculated at three heights using HYS-PLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory Model). The heights cho-sen were: 1) at surface level (80 m above ground) to give reprecho-sentative origins of air

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masses for the in-situ nephelometer measurements. 2) at 1 km, which can serve as a representative height for the boundary layer in which the majority of aerosol particles is present, thus providing a good estimation of the air mass origins for the column in-tegrated MFR measurements. 3) at 3 km for the presence of Sahara dust layers to be captured, if needed during specific case studies. We then selected sectors around the

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prevailing transport directions, to be used for the classification of the air mass origins. As seen in Fig. 4, five main sectors were used: (S) southern sector, to represent the influence from the African continent, with most trajectories coming from the south-west; (W) western sector, for air masses coming from either south-western European countries or north-western African countries having spent considerable time over the

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western Mediterranean or representing longer range transport from the Atlantic; (NW) northwestern sector, including the main part of central Europe; (N) Northern sector, used mainly to capture the transition between the Northwestern and Eastern sectors; and (E) eastern sector, to cover air-masses originating mainly from the most eastern-northeastern part of Europe, since trajectories coming from southeastern directions

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were quite rare. An additional sector (L) was also applied to represent those stagnant cases when trajectories showed air masses staying for an extended period over the neighboring areas without a prevailing direction. When trajectories were passing over different sectors the main sector chosen was the one over which air-masses spent most of their time, giving also additional weight to the fact that as one follows

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ries backwards there is a significant increase to their uncertainty.

Before proceeding to the more detailed investigation of the source regions, we give a brief description of the frequency and seasonality of the prevailing direction for air

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masses arriving at MAO, at both the surface and the 1 km height levels. For the days with available measurements, 40% of the trajectories originated from the E sector, whereas the other sectors were almost uniformly distributed with a small excess of the NW and N ones. During all seasons except winter, the E sector prevailed, and especially during summer its frequency reached 50%, while during winter the NW and

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N sectors retained each a frequency of 25–30%.

The main results of categorizing the aerosol optical properties according to the ori-gins of the air masses arriving at MAO station are presented in Table 2. Significant differences, in most cases characteristic of the sources present in the various sectors, are found (Fig. 5). Values were not assigned for the eastern-southeastern sector, since

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there were no trajectories originating from there, as already mentioned. At the borders of the sectors average values between adjacent sectors are used. A consistent dis-tribution pattern is evident for all three extensive quantities. The minimum values of AOD, σ_spand σ_bsp are in the NW sector, and then values increase moving clockwise, reaching a maximum in the E sector, and then decrease again for air masses from the

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S and the W sectors. In contrast, minimum values of ˚a_τ and ˚a_σ are found for the S sector and maxima for the N and E sectors ( ˚a_σ shows only minor variability and only for the S sector are values significantly different). Finally, β ratios have their minimum values in the S sector and maximum values in the NW sector.

More detailed information on these spatial patterns is revealed by calculating the

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frequency distribution of aerosol optical properties for each different sector (Fig. 6). As shown in Fig. 6a, AOD values higher than 0.45 are found to originate only from the E and L sector, which both have a relatively flat distribution, whereas a rather narrow distribution is revealed for the NW sector with a pronounced frequency peak at the 0.1–0.15 class. The distribution in the N sector represents a transition between the

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two most different sectors (E and NW). Finally, both the S and the W distributions appear to be bi-modal, with one mode describing the lower values and the other being partly shifted as one moves from the E sector maximum to the NW minimum. From the distributions in Fig. 6b one can clearly see the influence of the Sahara dust events

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on the size of aerosols, as revealed by the distinct peak around 0.4–0.6 found for the S sector. This maximum is less well defined for ˚a_σ, probably because most of the dust transport occurs at higher altitudes and does not influence surface aerosol properties as much as the column-integrated values (Formenti et al., 2001b; Andreae et al., 2002). The frequency distribution for ˚a_τ in the W sector is shifted to higher

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values serving again as a transition to the NW and N sectors, for which nearly identical and relatively broad distributions with maxima near 1.7 are found. Finally, a peak at the same position is present for the E and L sectors. The narrower frequency peak in these sectors suggests a more constant particle size distribution in the air masses arriving from these sectors. The similarity between the distributions in the E and L

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sectors is probably due to the fact that most of the L (local) trajectories actually arrive from easterly directions and that the two sectors include common pollution sources from eastern Balkan countries (L) and former Soviet Union countries (E). The same general pattern is evident for σ_spand σ_bsp(Figs. 6c, e) with minimum values originating from the N and NW sectors, while the distributions of the rest of the sectors are not

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separable.

3.3. Seasonality of aerosol optical properties

The seasonal variability of aerosol optical properties is mainly related to the seasonal characteristics of the production, transport and removal processes of aerosols over a specific region. In many studies (e.g. Michalsky et al., 2001; Holben et al., 2001;

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Alexandrov et al., 2002) a summer peak has been found for AOD, while larger aerosols dominate during winter.

Monthly means of aerosol optical properties at MAO and LAP are presented in Fig. 7. At MAO (Fig. 7a) a distinct annual cycle is seen with clear summer maximum (August) and winter minimum (December) for AOD, ˚a_τ and ˚a_σ. The second peak in October for

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˚a_τ can be attributed to particular days in October 1999 and 2001 with higher values for the Angstr ¨om exponents and slightly higher ones for AOD. The data show that, on a climatological basis, real background conditions are encountered at MAO only

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during November and December, with AOD down to 0.1 and ˚a below 1.2 indicating the possible influence from sea-spray aerosols. During summer, enhanced turbidity, the absence of wet removal processes, as well as the prevailing east sector under more stagnant meteorological conditions, result in the build-up of aerosols. The same conditions are also favorable to enhanced pollution near urban areas.

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In contrast, no clear annual cycle is revealed at LAP (Fig. 7b). This can be attributed to the fact that sources of pollution with different seasonal characteristics (central heat-ing, transportation, industrial activities etc.) are superimposed on the seasonality re-lated to the change of meteorological patterns. An extreme peak in August at LAP reconfirms that part of the seasonality at MAO is due to enhanced pollution, but one

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has still to bear in mind that the periods of measurements at the two sites are not the same and August 2001 has been an exceptional month, influenced by biomass burning from areas at the northern coast of the Black Sea (Salisbury et al., 2003; Balis et al., 2003b).

The seasonal variability of σ_spand σ_bsp (Fig. 7c) is quite different. Following a

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mum in August, there is an even larger one in the fall (November), whereas a minimum is seen during spring. However, it should be mentioned that values for April, May and June are mainly from 2000 and that during this period the lowest values of the whole data set are found. The seasonal cycle of the planetary boundary layer (PBL) thickness (Balis et al., 2003a) could be responsible for the fall and winter maximum in σ_sp. The

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PBL is shallower in fall and winter and thus aerosols are confined to a thinner layer. In contrast, ˚a_σ is consistent with the seasonality in ˚a_τsince both show the same summer maximum, with the specific annual cycle being much more distinct for ˚a_σ. The same pattern is also followed by β (Fig. 7d).

3.4. Diurnal variability of aerosol optical properties

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To investigate the diurnal variability of the aerosol optical properties, we used higher resolution data (1-min and 2-min averages of the quantities measured directly and indi-rectly by the two instruments). A distinct diurnal cycle is observed for all quantities, as

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seen in Fig. 8. AOD values decrease at both sites (Fig. 8a) around 06:00–08:00 UTC, reach a minimum at about 12:00–14:00 UTC and then start increasing again during afternoon (12:00 UTC corresponds to 10:28 solar time at MAO). The column ˚angstr ¨om exponents, ˚a_τ, (Fig. 8b) also show a decrease in the morning, more intense at MAO than at LAP, and then they increase until 14:00 UTC, when they are subject to an

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abrupt decrease. Observing AOD for individual days, it is seen that there are no abrupt changes within the day and specific patterns are found. The most common patterns are those of AOD decreasing during the day and either reaching a plateau during afternoon or increasing again, but not reaching the same values as in the early morning.

The diurnal variation from the nephelometer data covers the full 24-hour period,

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but the results indicate more or less the same behavior. Both σ_sp and σ_bsp (Fig. 8c) decrease around 08:00 UTC, reach a minimum value at about 14:00 UTC and then increase until 20:00–22:00 UTC, after which they remain on a plateau during the whole night. The pattern for ˚a_σ is similar (Fig. 8d), but shows a phase shift of about 2– 3 h, with maxima and minima occurring earlier than for the other parameters. The

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minimum occurs at 06:00 UTC, then values rise until 12:00 UTC and then a decrease is observed during afternoon. A similar pattern is found for β with minimum and maximum preceding those of ˚a_σ.

Gebhart et al. (2001) refer to five different diurnal patterns for optical properties of aerosols at various stations in the US, mainly related to the relationship between RH

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and scattering. Many of the patterns were linked to local sources or local meteorol-ogy whereas factors causing diurnal variability in particle concentration or composition are also important. At MAO and LAP, the diurnal variability of the optical properties of aerosols (Fig. 8) follows the heating of the surface by the sun, suggesting that this pattern is mainly driven by the effect of relative humidity (RH) on the size and the

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position of aerosols. Numerous studies (H ¨anel, 1976; Fitzgerald et al., 1982; Charlson et al., 1984; Horvath, 1996) have focused on the change of particle size with RH for different types of atmospheric aerosols.

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RH measurements of the nephelometer. The instrument was located in a small room directly under the roof of the building, which generally was a few degrees warmer than the ambient temperature, so that internal RH was somewhat lower than that of the ambient air. As seen in Fig. 9, RH has a distinct diurnal cycle in general agreement with those of the aerosol optical properties. More specifically, regression analysis shows a

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strong correlation between RH with σ_spand σ_bsp(r2= 0.98 and 0.92, respectively) with a time delay of 1–1.5 h and a strong anticorrelation with β (r2 = −0.96) at zero lag. The anticorrelation with ˚a_σ is weaker (r2 = −0.74) possibly due to the fact that ˚a_σ is influenced by the instrumental noise on the scattering coefficients. The additional time delay of ˚a_τ in comparison with ˚a_σ can be attributed to the fact that since the heating

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of the atmosphere is taking place from the surface and upwards, it takes some time to affect the relative humidity of the column that the MFR sees.

But can the RH variability explain the whole of the diurnal cycle of the optical prop-erties? To answer this question, a correction factor f(RH) describing the hygroscopic growth of the aerosol particles with increasing RH is calculated, according to the

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tion f (RH)= a·(1−RH/100)b(Kasten, 1969; H ¨anel, 1976). The choice of the constants

a and b vary for different chemical composition of the aerosols (Day and Malm, 2001).

Since no representative values are known for MAO, different constants (Day and Malm, 2001; Clarke et al., 2002) were applied and σ_sp was corrected according to the f (RH) (Fig. 9). Depending on the choice of the constants 45–60% of the diurnal cycle is

20

explained by RH, but a considerable part still remains unexplained.

This part could be attributed to the contribution of local circulation systems persis-tent under certain meteorological conditions. Since both measuring sites (LAP and MAO) are very close to the sea, under weakening of the synoptic winds local circula-tion systems develop, which often lead to a sea-breeze circulacircula-tion cell. This circulacircula-tion

25

pattern is stronger and appears more often during the warm period. Its presence re-sults in a shallower PBL (e.g. Melas et al., 1998) and in a diurnal variation of both wind speed and wind direction. In a typical sea breeze pattern it is expected that the wind speed reaches maximum values around 08:00–09:00 UTC and remain constant until

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the afternoon (16:00–17:00 UTC) for places that are a few kilometers inland. When the sea-breeze flow pattern is established both at the surface and up to the mixing height, the boundary-layer air originates from the sea. This pattern can introduce different aerosol sources during most of the day compared to the sources that are associated with the synoptic flow over the area. The diurnal variability of the ˚angstr ¨om exponent

5

shown in Fig. 8 indicates changes in the aerosol type and is in phase with the evolution of the sea-breeze cell.

Additional results are derived by sorting the diurnal variability by seasons and trajec-tory origins. Thus, extracting the diurnal cycles for pairs of months (not shown here) one can see that during winter-spring (November–December, January–February and

10

less during March–April), when the maximum diurnal range of RH is observed, the am-plitude of the diurnal cycle of both σ_spand σ_bsptakes its maximum value as well. When sorting the diurnal variability by the trajectory origins it is shown that when air masses come from the S–SW sectors then the diurnal cycle of σ_sp and σ_bsp is more intense. In combination with the fact that the decrease of the values is prolonged during the

15

afternoon, this possibly reflects the local sea breeze system.

4. Further analysis

4.1. Comparison between rural and urban measurements – Estimation of contribu-tions from local pollution

As already mentioned, the key difference between the two sites is the fact that

Thessa-20

loniki (LAP) is the main urban center of the region, and is therefore impacted by local pollution sources, while MAO is remote enough to be considered as a rural site. On the other hand, the sites are close enough to each other so that they are influenced simultaneously from medium- and long-range transport. This allows us to estimate the contribution of local pollution to the aerosol radiative effects at LAP, without of course

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MAO.

For the period when both sites were operating simultaneously, AOD values at the two sites show significant covariance (r2=0.76 at 500 nm and 0.69 for ˚a_τ), partly bearing out the assertion above (Fig. 10). Even though not evident in Table 1 due to the use of the entire periods for both sites instead of their common period, AOD values over LAP

5

were on average higher than over MAO, reflecting local pollution in Thessaloniki (values at LAP are generally above the 1:1 line). Assuming a simple additive effect of the urban pollution, the mean of the AOD differences would express the contribution of the pollution, provided that clear days and days with transport from Thessaloniki to MAO are excluded. Also, one has to consider that on a climatological basis the differences in

10

transport from remote sources at the two sites are not significant. In order to investigate the above, the differences of AOD at MAO and LAP were categorized according to the direction of the arriving air masses. In general, small differences (many of them not exceeding the uncertainty of the measurements) are found for all sectors except the Eastern one. This is a combination of the fact that some sectors (NW–N) were related

15

to the transport of cleaner air masses (Sect. 3.2) and that in the sectors from SW to NW urban pollution at Thessaloniki affects MAO. On the contrary, for air masses from the E sector, the differences become significant and more consistent. These days are more frequent during summers, when also meteorological conditions favor the trapping of pollution, and during which there is no transport of urban pollution to MAO.

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Thus, when only the days with air masses from the E sector are considered, a linear regression analysis results in a slope of 0.9±0.14 indicating that there is indeed a constant shift to higher values for LAP that could on average give an estimation of the local pollution sources at Thessaloniki. This contribution is acquired from the intercept, 0.19±0.05 at 500 nm, leading to a contribution of 35±10% for the average AOD over

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LAP. For the rest of the cases the contribution, calculated from the mean of the AOD differences at the two sites, varies between 3–10%.

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4.2. Estimation of aerosol scale height

The aerosol scale height, which is the equivalent depth of the optically active aerosol layer of the atmosphere at an assumed constant pressure equal to the surface pressure, can be estimated by combining the extinction coefficient, s_ep, and the AOD at MAO. In general, if a linear relationship between the two parameters exists

5

(AOD=H*σ_ep+b), then the slope of the regression line gives the aerosol scale height, under the assumption that aerosols are homogeneously concentrated within the lower part of the atmosphere, near the ground and up to the height, H. The variance ex-plained by the regression gives an indication of how well the column extinction is rep-resented by a measurement at the bottom of the boundary layer. The intercept, on

10

the other hand, represents more or less constant contributions to extinction by free tropospheric and stratospheric background aerosols.

However, for the calculation of s_ep apart from σ_sp the aerosol absorption coefficient,

σ_abs, is also needed. Shettle and Fenn (1979) provide the single scattering albedo,

ω, for various types of aerosols, ranging from 0.7 (urban) to 0.98 (maritime) with ω

15

equal to 0.94 and 0.96 for rural and tropospheric background, respectively. Moreover, estimations of ω over the Eastern Mediterranean show mean values within the range of 0.85–0.90 (Kouvarakis et al., 2002; Lelieveld et al., 2002; Formenti et al., 2002a; 2002b). Thus, assuming the general case of moderately absorbing aerosols (ω=0.9),

σ_ep would be 10% higher than σ_sp, which leads to a corresponding 10% reduction to

20

the calculated aerosol scale height. Nevertheless, for the regressions below, σ_sp will be used instead of s_ep since an exact value for ω is not available, and it must be kept in mind that the corrected value for H is H/(2 − ω). Application of the correction for (ω=0.9) will also be provided.

In the scatter plot between σ_sp and AOD at 550 nm for the whole period (Fig. 11)

25

a great dispersion of values can be seen, thus not fully satisfying the assumption of linearity for the determination of H (AOD at 550 was derived by Angstr ¨om’s power law approximation, τ(λ) = βλ− ˚a, after constants α, β, were calculated). Nonetheless, the

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regression for the whole of the available data yielded a mean aerosol scale height of 2.1±0.2 km (1.9±0.18 km, for ω=0.9). When we stratified the data seasonally, the aerosol scale height was found to be 1.1±0.13 km (0.96±0.11 km, for ω=0.9) during the colder period (October–March) with 54% of AOD variance explained by the variability of the near-surface aerosols, whereas, during the warmer months, (April–September)

5

H went up to 2.6±0.25 km (2.3±0.22 km, for ω=0.9). The greater scatter of the values

during the warm season reflects the more variable aerosol loading and the greater fluctuation of the boundary layer thickness.

We also calculated the aerosol scale height for those individual months when data coverage was sufficient for both AOD and σ_sp. As seen in Fig. 12, a distinct seasonality

10

with a peak of 2.7 km (2.5 km, for ω=0.9) in August–September (coinciding with the peak in AOD seasonal cycle) is seen, whereas during the cold months (November– February) H is between 0.5–1 km. The corrected heights remain well within the stan-dard error of the estimations. The seasonal cycle of the aerosol scale height relates to the seasonal change in the boundary layer thickness as shown by individual

es-15

timations of the PBL by LIDAR and radiosondes at Thessaloniki. More specifically, the PBL during 2001 varied between 0.3–0.5 km during winter, whereas for summer it had values about 1.5–1.7 km, exceeding 2 km under certain circumstances (Balis et al., 2003a). This result is consistent with the assumption that most of the aerosols are present within the boundary layer, and that there is a lesser contribution to scattering

20

from free tropospheric aerosols. This is additionally supported by the relatively small value of the regression intercept (0.049–0.057 for optical depth at 550 nm), indicat-ing an average contribution of 24–28% of the total AOD from aerosols outside of the boundary layer, part of which can be attributed to the transport of dust from the Sahara desert.

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5. Conclusions

Aerosol optical properties from two sites in Northern Greece, the first at Thessaloniki (LAP), the main city of the region, and the second at Ouranoupolis (MAO), 100 km to the east, have been analyzed in order to provide information about the climatological characteristics of aerosol optical properties. The data cover a time span of 3 years.

5

The mean value of 0.23 for AOD at 500 nm at both sites is well within the range of values observed previously in the area (Formenti et al., 2001b). During summer, AOD values increase considerably, remaining persistently between 0.3 and 0.5, while during specific cases they go up to 0.7–0.8. The higher values of AOD are mainly associated with fine aerosols as indicated by the ˚a_τexponents. At MAO, a mean value

10

of 65±40 Mm−1 for σ_sp at 550 nm reflects the impact of continental pollution on the region. During the colder months values are usually well above 100 Mm−1, reaching even 250 Mm−1under certain circumstances. The level of σ_spis well above the limits of 10–30 Mm−1 reported for unpolluted marine air (Formenti et al., 2001 and references therein). This limit is exceeded during 80% of the days for which measurements were

15

available, and for 50% of the days values are above the mean value of 57 Mm−1 given by Seinfeld and Pandis (1998) for the average continental background. The frequency distributions of AOD, σ_sp and σ_bsp have revealed the existence of different modes of aerosol loading associated with background conditions, average continental aerosol concentrations, and highly polluted air masses from either local and regional sources

20

or from longer range transport.

The investigation of source regions via air mass trajectory analysis has shown that enhanced AOD, σ_sp and σ_bsp are found for the E sector. Observations of enhanced SO₂over Southeastern Europe by GOME (Eisinger and Burrows, 1998) as well as the fact that during NE directions about 70% of the SO₂column can be attributed to lignite

25

combustion in power plants in Bulgaria and Romania (Zerefos et al., 2000), can help to explain the maxima in aerosol loadings from the easterly sector. Biomass burning from areas at the northern coast of the Black Sea (Salisbury et al., 2003; Balis et

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al., 2003b) may also contribute episodically. Cleaner conditions, associated with fine aerosol particles, are found for the NW direction, in spite of the presence of the most industrialized countries of Central Europe being in this sector. The reason for this could be the meteorological conditions during which NW air mass trajectories reach Northern Greece, namely increased wind speed and atmospheric washout, and the fact that this

5

path is often associated with subsidence from the upper troposphere (Gerasopoulos et al., 2001). The influence of Sahara dust events is clearly shown by both ˚a exponents and backscatter ratio β. The values of ˚a_τ for the S sector (Fig. 6b) are distributed around 0.4, which is typical of mineral dust (Kaufman, 1993), while the corresponding ˚a_σexponents from scattering are shifted to higher values, since dust layers are present

10

mainly at elevated altitudes. The coarse dust particles are also responsible for the enhanced scattering for the S sector.

The temporal variability of aerosol optical properties at two time scales was also investigated. A distinct summer maximum was revealed for AOD and ˚a_τat MAO, but the seasonality at LAP was masked by the seasonal variability of local pollution sources.

15

Only during November and December can real background conditions be observed at MAO, with AOD down to 0.1 and ˚a exponents below 1.2 indicating the possible influence from sea-spray aerosols. The seasonality is mainly driven by the fact that during summer 50% of the trajectories (for the days that measurements were available) came from the E sector. This fact, in combination with enhanced turbidity, the absence

20

of wet removal processes and conditions favorable to enhanced pollution, leads to the build-up of aerosols during summer. A diurnal cycle of all properties was evident. In the morning, AOD, σ_sp and σ_bsp decrease simultaneously with humidity and reach a minimum at mid-day. About 45–60% of the diurnal cycle amplitude was explained by the effect of humidity on the size of hygroscopic aerosols. The rest of the variability

25

was attributed to the local sea breeze system that results in a shallower PBL and in a diurnal variation of both wind speed and wind direction, thus introducing different aerosol sources than those resulting from the synoptic flow over the area.

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tribution of the local pollution sources to Thessaloniki’s AOD was attempted. During summer, when the effect of urban pollution is favored by meteorological conditions, a constant shift by 0.19±0.05 at 500 nm was found, leading to a contribution of 35±10% for the average AOD over LAP, while in general it ranges between 3–10%. Finally, the equivalent thickness of the optically active aerosol layer (aerosol scale height) was

5

found to be related to the height of the boundary layer, with values between 0.5–1 km during winter and up to 2.5–3 km during summer.

Acknowledgement. This research was financially supported by the Max Planck Society,

Ger-many.

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Zerefos, C. S., Kourtidis, K. A., Melas, D., Balis, D., Zanis, P., Mantis, H. T., Repapis, C., Isaksen, I., Sundet, J., Herman, J., Bhartia, P. K., and Calpini, B.; Photochemical Activity and Solar Ultraviolet Radiation Modulation Factors (PAUR): An overview of the project, J.

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Geophys. Res., 10.1029/2000JD000134, 2002.

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EGU 2003

Table 1. Basic statistical quantities from daily values for: (a) aerosol optical depth (AOD)

calculated at MAO (June 1999–Auguat 2000 and July 2001–March 2002) and LAP (February 2001–March 2002), (b) scattering (σ_sp) and backscattering (σ_bsp) coefficients at MAO (June 1999–March 2002),(c) Angstr ¨om exponents from optical depths ( ˚aτ) and scattering coefficients

( ˚aσ), and backscatter ratio (β). Averages are accompanied by their standard deviation. Note

that no direct comparison between the stations is feasible from this table since the values do not correspond to a common period (see Sect. 4.1 for a comparison)

Table 1. Basic statistical quantities from daily values for: a) aerosol optical depth (AOD) cal-culated at MAO (Jun 99 – Aug 00 and Jul 01 – Mar 02) and LAP (Feb 01 – Mar 02), b) scat-tering (σsp) and backscattering (σbsp) coefficients at MAO (Jun 99 – Mar 02), c) Angström ex-ponents from optical depths (åτ) and scattering coefficients (åσ), and backscatter ratio (β). Av-erages are accompanied by their standard deviation. Note that no direct comparison between the stations is feasible from this table since the values do not correspond to a common period (see section 4.1 for a comparison).

a) AOD MAO 414 nm 500 nm 614 nm 671 nm 867 nm Average 0.30 ± 0.16 0.23 ± 0.13 0.17 ± 0.10 0.15 ± 0.08 0.11 ± 0.06 Maximum 0.92 0.69 0.53 0.48 0.47 Minimum 0.042 0.028 0.025 0.025 0.020 LAP Average 0.32 ± 0.20 0.23 ± 0.15 0.14 ± 0.10 0.11 ± 0.09 0.10 ± 0.07 Maximum 1.02 0.77 0.58 0.54 0.54 Minimum 0.073 0.050 0.012 0.010 0.026 b) σsp (Mm-1) σbsp (Mm-1) MAO 450 nm 550 nm 700 nm 450 nm 550 nm 700 nm Average 91 ± 54 65 ± 40 44 ± 27 7.7 ± 4.6 6.4 ± 3.5 5.3 ± 2.8 Maximum 337 246 161 26.0 21.1 17.4 Minimum 9.9 8.3 5.6 0.1 0.8 0.9 c) åτ åσ β (867 nm/414 nm) (700 nm/450 nm) 550 nm

MAO LAP MAO MAO

Average 1.4 ± 0.4 1.6 ± 0.3 1.7 ± 0.4 0.1 ± 0.02

Maximum 2.25 2.21 2.33 0.16